Conventional pulsed energy detectors are typically of two types: matched filter or crystal video. A matched filter makes use of detailed a priori knowledge of the pulse being detected. Pulse shape, frequency, and sometimes phase are used to construct the detector. Matched filter detectors offer optimal sensitivity, but do not function well for frequencies or pulse widths other than the original design point.
Crystal video receivers offer performance over a range of frequencies; however, the video filter is targeted at a particular pulse width. The sensitivity is not as good as a matched filter receiver and degrades as a function of the radio frequency (RF) bandwidth/Video bandwidth ratio.
Important criteria for pulsed energy receivers are sensitivity, instantaneous bandwidth (IBW), and false alarm rate (FAR). Sensitivity specifies the relationship between pulse power, probability of detection (PD) and noise density (N0) for a given type of pulse. Often sensitivity is specified for a pulse power to input noise power ratio, which is called the signal to noise ratio (SNR).
Pulses may be classified as modulated or unmodulated. Pulses may be modulated for pulse compression or reduced detectability. Unmodulated pulses are essentially time-gated sections of a continuous wave (CW) signal.
Radar (radio detection and ranging) and sonar (sound navigation ranging) are examples of systems which must detect pulsed energy in the presence of background noise. Radar terminology is used here, although the principals and techniques apply to a wide variety of applications.
Pulse compression allows a radar to use a long pulse to achieve large radiated energy per pulse, while obtaining a range resolution of a short pulse of wide bandwidth. A radar system achieves this condition by modulating the long pulse of width T to achieve a bandwidth B>>1/T. The received signal is passed through a matched filter to produce a compressed pulse of width 1/B. The pulse compression ratio is equal to BT. Frequency and phase modulations are typically used for pulse compression.
Spread spectrum techniques may be used to reduce detectability of radar pulses by unintended parties. A conventional spread-spectrum system may employ a modulation technique in which a narrow-band signal (a long pulse) is spread over a broad frequency range using a spreading function. Such a signal may contain a significant amount of total energy while maintaining a small energy at any given frequency, even below the level of background noise. The signal thus blends into the noise. Since the energy contained in the signal is very low at any given frequency, the signal is difficult to detect. Spread spectrum detectors must, therefore, utilize techniques for improving pulse detection sensitivity in a noisy environment.
In a direct-sequence type spread spectrum system having a signature sequence, the bandwidth of the spread-spectrum signal is usually much larger than that of the pulse envelope. A typical receiver used with binary direct-sequence spread-spectrum modulation and having an additive white Gaussian noise channel (thermal noise only) is a correlation receiver. In such a receiver, a received signal is multiplied in a frequency conversion process and the product is integrated over an interval that approximates the pulse duration.
A conventional receiver may include a receive antenna, an RF preamplifier, mixers that operate using a local oscillator (LO), an intermediate frequency (IF) low pass filter, an analog-to-digital (A/D) converter having a high sampling rate, a memory for storing data having a predetermined resolution, processors for modifying the data, such as by using a Fast Fourier Transform (FFT), and digital signal processors (DSPs) for additional processing, such as filtering or additional FFTs. To maximize the bandwidth most efficiently, the sampling is usually done in quadrature to create I and Q channels, as is known.
A “channel” may include a discrete channel, a continuous channel defined on discrete time instants, or a waveform channel defined on a continuum of time points.
A “noisy channel” is one for which the channel's output symbol is not completely determined by the channel's input symbol; only some probability distribution on the set of output symbols is determined by the input symbol. If the probability is independent of previous inputs or outputs from the channel, the channel is called “memoryless.” Information can be sent reliably through a discrete noisy channel by use of elaborate crosschecking techniques known as error control codes. A noisy channel may also have constraints that can identify codes to be treated separately from the error control codes.
A channel's capacity is generally known to be the maximum rate at which information can be transmitted through the channel. At any rate below channel capacity, an error control code can be designed to balance an amount of error control and a throughput for a channel. Well-known error control codes may control and/or operate with various other parameters. A selection of coding for a channel may also relate to whether information is fixed-length, variable length, infinite length, etc.
Compression is a technique which allows a larger volume of information to be passed through a channel of fixed capacity. Compression methods are classified as lossless or lossy. Lossless compression allows exact recovery of the original data. Lossy compression discards unimportant features of the original data, allowing greater compression ratios than lossless techniques.
A variable-bandwidth frequency division multiplex communication system is known, where a sampling frequency is a multiple of the channel frequency interval A f. However, such a system results in aliasing and other frequency-based sampling problems concerning transmultiplexers, so that channel bandwidth is less than channel spacing.
The trend in modern radar systems is toward a use of complex signals with agility over several parameters. This requires implementation of good detection sensitivity and wide bandwidths to meet increasing performance demands. Existing digital systems have either poor sensitivity or limited bandwidth, and little or no compression capability. What is needed is the development of wideband digital receivers with low power consumption and improved sensitivity, and improved compression capabilities.